Manufacturing Technician applicants have rated the interview process at Reckitt with 3.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 50% positive. To compare, the company-average is 67.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Manufacturing Technician roles take an average of 25 days to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at Reckitt overall takes an average of 24 days.
Common stages of the interview process at Reckitt as a Manufacturing Technician according to 2 Glassdoor interviews include:
One on one interview: 50%
IQ intelligence test: 25%
Skills test: 25%
Here are the most commonly searched roles for interview reports -
I applied through college or university. The process took 4 weeks. I interviewed at Reckitt in Sep 2014
Interview
Initial communication was through career fair at university. Received email a week or so later to set up time for on campus interview. The interview was one-on-one and the interviewer provided lots of information on different locations of companies.
Interview questions [1]
Question 1
When was the time that you applied your technical skill well in a group setting?
Easy like most interviews just generally talk about experience and why you want the job and what makes you stand out compared to everyone else who wants the job and what level is my experience
I applied through college or university. The process took 3 weeks. I interviewed at Reckitt
Interview
Approached the company reps through a university fair. They got back to me the day before the interview date, apologizing and asking interviewees to schedule their interviews asap. The interviewer was an industrial engineering major fresh out of college and had no actual knowledge of manufacturing engineering. He was unenthusiastic and went through his questions as quickly as possible. The questions were typical behavioral questions.
Interview questions [1]
Question 1
Describe a time when you used a large data set to recommend a suggestion. (I had trouble understanding what he was asking)